Translation of abstract (English)

Structural rearrangements in proteins are essential for biological function. Often, these are complex transitions, involving a multitude of pathways through a high-dimensional conformational space. As yet, no experiments are available to identify the possible mechanisms of these transitions. Direct computer simulations of protein dynamics can neither be used, as the simulation time presently accessible to them is several orders of magnitude below the timescale on which complex transitions occur. In the present work, a divide-and-conquer approach based on Transition Networks (TN) is proposed. TN are weighted graphs, which connect the experimentally determined end-state structures by a dense network of sub-transitions (the network edges) via low-energy intermediates (the network vertices). It is shown here how the computation of TN, previously feasible only for small polypeptides, can be achieved for a protein. To generate the TN vertices, an efficient hierarchical procedure is developed which uniformly samples the conformational subspace relevant to the transition. As the determination of TN edge weights is computationally very expensive, a graph-theoretical approach is presented here which allows global network properties to be determined while only having to compute a small subset of edge weights. Following this approach, algorithms are presented to compute the best path connecting, and the energy ridge separating the transition end-states. The approach is illustrated on the conformational switch of Ras p21. The 32 best transition pathways with rate-limiting barriers up to 15 kcal/mol above the globally-best pathway were determined, as well as the two main energy ridges, which involve rearrangements of the Switch I and Switch II loops, respectively. Based on these results, three competing pathways for the rearrangement of Switch I were identified, in all of which Tyr32 is threaded underneath the protein backbone. Subsequently, the rate-limiting unfolding of Switch II occurs, which follows a similar pattern among the best paths and progresses from the N-terminal to the C-terminal end. Despite these similarities, the precise order and the detailed realization of conformational events in Switch I and II varies, showing that complex conformational transitions in proteins may indeed occur via multiple pathways. As the Ras p21 application demonstrates, the methodology developed here is useful to understand very complex mechanisms in proteins independent of their typical timescale. This represents a significant methodological progress in the field of molecular biophysics.